Alexandros Beskos

Science (Statistics)

Visiting Associate Professor


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Visiting Associate Professor of Science (Statistics) Alexandros Beskos received his PhD in Statistics at Lancaster University. He was a postdoctoral fellow at the Mathematics Institute and Department of Statistics, University of Warwick, after which he has been a Lecturer, Senior Lecturer and Reader in Statistics at University College London. Prior to visiting Yale-NUS College, Visiting Assoc Prof Beskos has been a Reader at University College London.

Assoc Prof Beskos is a Statistician & Data Scientist. His research interests are in Bayesian Statistics, Markov-Chain Monte Carlo, Filtering Algorithms, Machine Learning, Inverse Problems, Data Assimilation, Applications in Finance, Biostatistics, and Atmospheric Sciences.

His interdisciplinary work includes collaborations in the fields of: Applied Mathematics, in the area of Inverse Problems; Biology, in the area of Epigenetics (Methylation); Biostatistics; Finance, in the area of Stochastic Volatility.

Bayesian inference for partially observed Stochastic Differential Equations driven by fractional Brownian motion, with Joseph Dureau, Kostas Kalogeropoulos. Biometrika, 102, 4(2015), 809-827.

Bayesian inference for Duplication-Mutation with Complementarity Network models, with Ajay Jasra, Adam Persing, Kari Heine, Maria De Iorio. Journal of Computational Biology, 22, 11(2015), 1025-1033.

Sequential Monte-Carlo methods for high-dimensional Inverse Problems: a case study for the Navier-Stokes equations, with Nikolas Kantas, Ajay Jasra. SIAM/ASA Journal of Uncertainty Quantification, 2, 1(2014), 464-489

On the stability of Sequential Monte-Carlo methods in high dimensions, with Dan Crisan, Ajay Jasra. The Annals of Applied Probability, 46, 4(2014), 1396-1445.

Advanced MCMC methods for sampling on diffusion pathspace, with Kostas Kalogeropoulos, Erik Pazos. Stochastic Processes and their Applications, 123, 4(2013), 1415-1453.

Optimal tuning of the Hybrid Monte-Carlo, with Natesh Pillai, Gareth Roberts, Jesus Maria Sanz-Serna, Andrew Stuart. Bernoulli, 19, 5A(2013), 1501-1534.

epsilon-strong simulation of the Brownian path, with Stefano Peluchetti, Gareth Roberts. Bernoulli, 18, 4(2012), 1223-1248.

Hybrid Monte-Carlo on Hilbert spaces, with Frank Pinski, Jesus Maria Sanz-Serna, Andrew Stuart. Stochastic Processes and their Applications, 121, 10(2011), 2201-2230.

Optimal scalings for local Metropolis-Hastings chains on nonproduct targets in high dimensions, with Gareth Roberts, Andrew Stuart. The Annals of Applied Probability, 19, 3(2009), 863-898.

Monte-Carlo maximum likelihood estimation for discretely observed diffusion processes, with Omiros Papaspiliopoulos, Gareth Roberts. The Annals of Statistics, 37, 1(2009), 223-245.

Retrospective exact simulation of diffusion sample paths with applications, with Omiros Papaspiliopoulos, Gareth Roberts. Bernoulli, 12, 6(2006), 1077-1098.

Exact simulation of diffusions, with Gareth Roberts. The Annals of Applied Probability, 15, 4(2005), 2422-2444.

Exact and computationally efficient likelihood-based estimation for discretely observed diffusion processes (with discussion), with Omiros Papaspiliopoulos, Gareth Roberts, Paul Fearnhead. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 68, 3(2006), 333-382.

YSC3252: Statistical Computing
YSC4225: Stochastic Processes and Models (SPaM)